Comparative Immunohistochemical Study of the Stroma of Serous and Mucinous Cystic Neoplasms
Bibliographic record
Abstract
OBJECTIVES: Serous and mucinous cystic neoplasms (SCNs/MCNs) are the most common true cystic neoplasms of the pancreas and occur more frequently in women. The aim of this study was to characterize the stroma of SCNs to compare its phenotype with that of MCNs. METHODS: A total of 12 SCNs and 5 MCNs were analyzed immunohistochemically using the following antisera: progesterone receptor (PR), estrogen receptor (ER), inhibin, CD10, and vimentin. Normal pancreatic tissue (17 cases) and ductal adenocarcinomas of the pancreas (3 cases) were used as controls. RESULTS: Eight of 12 patients with SCNs and all 5 patients with MCNs were women. For SCNs, the stroma was sclerotic and paucicellular and showed focal moderate to strong reactivity for PR. Estrogen receptor, CD10, and inhibin were virtually negative. For MCNs, the stroma was more cellular and ovarianlike and showed a larger number of PR-positive cells with focal expression of ER and inhibin. Vimentin was expressed in all stromal cells in both groups. CONCLUSIONS: Both SCNs and MCNs contain PR-positive stromal cells. In view of the aforementioned clinical and immunophenotypical similarities, we suggest that in SCNs and MCNs, the stromal framework is similar in origin and/or differentiation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".